基于混沌映射的自适应樽海鞘群算法

针对樽海鞘群算法收敛速度慢、易陷入局部最优等问题,提出了一种基于混沌映射的自适应樽海鞘群算法。在种群初始化阶段引入混沌映射来增强种群的多样性,提高算法的收敛速度;改进领导者的更新方式,同时加入自适应权重,提高算法的探索和开发能力;改进追随者的位置更新方式,减少追随者的盲目性。通过对10个测试函数进行仿真实验,并与其他优化算法进行比较,实验结果表明,在不改变原有时间复杂度的前提下,提出的算法在收敛速度和寻优精度上有较大的提升,具有更好的优化性能。

Adaptive Salp Swarm Algorithm Based on Chaotic Map

In this paper,aiming at slow convergence speed and tendency to fall into local optimum of the Salp Swarm Algorithm,which an adaptive Salp Swarm Algorithm based on chaotic mapping(CASSA)is proposed.Firstly,this paper introduced a chaotic mapping to enhance the diversity of the population and improve the convergence speed of the Salp Swarm Algorithm.Secondly,CASSA enhanced the update method of leaders and added adaptive weights to improve algorithm capabilities of exploration and development.Thirdly,CASSA also modified the location update method of followers to reduce followers’blindness.Finally,through simulation experiments on 10 test functions and comparison with other optimization algorithms,the experimental results show that the proposed algorithm has a greater improvement in convergence speed and optimization accuracy without changing the original time complexity and has a better optimization performance.